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This manuscript aims to contribute to the next phase of mechanisms of behavior change (MOBC) science on alcohol or other drug use. Specifically, we encourage the transition from a basic science orientation (i.e., knowledge generation) to a translational science orientation (i.e., knowledge application or Translational MOBC Science). To inform that transition, we examine MOBC science and implementation science and consider how these two research areas can intersect to capitalize on the goals, strengths, and key methodologies of each. First, we define MOBC science and implementation science and offer a brief historical rationale for these two areas of clinical research. Second, we summarize similarities in rationale and discuss two scenarios where one draws from the other-MOBC science on implementation strategy outcomes and implementation science on MOBC. We then focus on the latter scenario, and briefly review the MOBC knowledge base to consider its readiness for knowledge translation. Finally, we provide a series of research recommendations to facilitate the translation of MOBC science. These recommendations include: (1) identifying and targeting MOBC that are well suited for implementation, (2) use of MOBC research results to inform broader health behavior change theory, and (3) triangulation of a more diverse set of research methodologies to build a translational MOBC knowledge base. Ultimately, it is important for gains borne from MOBC science to affect direct patient care, while basic MOBC research continues to be developed and refined over time. Potential implications of these developments include greater clinical significance for MOBC science, an efficient feedback loop between clinical research methodologies, a multi-level approach to understanding behavioral change, and reduced or eliminated siloes between MOBC science and implementation science.

Background: Primary care (PC) offers an opportunity to treat opioid use disorders (OUD). The Substance Use Symptom Checklist ("Checklist") can assess DSM-5 substance use disorder (SUD) symptoms in PC. Objective: To test the psychometric properties of the Checklist among PC patients with OUD or long-term opioid therapy (LTOT) in Kaiser Permanente Washington (KPWA). Design: Observational study using item response theory (IRT) and differential item functioning (DIF) analyses of measurement consistency across age, sex, race and ethnicity, and receipt of treatment. Patients: Electronic health records (EHR) data were extracted for all adult PC patients visiting KPWA 3/1/15–8/30/2020 who had ≥ 1 Checklist documented and indication of either (a) clinically-recognized OUD (i.e., documented OUD diagnosis and/or OUD medication treatment) or (b) LTOT in the year prior to the checklist. Main measure: The Checklist includes 11 items reflecting DSM-5 criteria for SUD. We described the prevalence of 2 SUD symptoms reported on the Checklist (consistent with mild-severe DSM-5 SUD). Analyses were conducted in the overall sample and in two subsamples (clinically-recognized OUD and LTOT only). Key Results: Among 2007 eligible patients, 39.9% endorsed ≥ 2 SUD symptoms (74.3% in the clinically-recognized OUD subsample and 13.1% in LTOT subsample). IRT indicated that a unidimensional model for the 11 checklist items had excellent fit (comparative fit index = 0.998) with high item-level discrimination parameters for the overall sample and both subsamples. DIF across age, race and ethnicity, and treatment was observed for one item each, but had minimal impact on expected number of criteria (0–11) patients endorse. Conclusions: The Substance Use Symptom Checklist measured SUD symptoms consistent with DSM-5 conceptualization (scaled, unidimensional) in patients with clinically-recognized OUD and LTOT and had similar measurement properties across demographic subgroups. The Checklist may support symptom assessment in patients with OUD and diagnosis in patients with LTOT. [ABSTRACT FROM AUTHOR]

Behavioral coding is increasingly used for studying mechanisms of change in psychosocial treatments for substance use disorders (SUDs). However, behavioral coding data typically include features that can be problematic in regression analyses, including measurement error in independent variables, non normal distributions of count outcome variables, and conflation of predictor and outcome variables with third variables, such as session length. Methodological research in econometrics has shown that these issues can lead to biased parameter estimates, inaccurate standard errors, and increased Type I and Type II error rates, yet these statistical issues are not widely known within SUD treatment research, or more generally, within psychotherapy coding research. Using minimally technical language intended for a broad audience of SUD treatment researchers, the present paper illustrates the nature in which these data issues are problematic. We draw on real-world data and simulation-based examples to illustrate how these data features can bias estimation of parameters and interpretation of models. A weighted negative binomial regression is introduced as an alternative to ordinary linear regression that appropriately addresses the data characteristics common to SUD treatment behavioral coding data. We conclude by demonstrating how to use and interpret these models with data from a study of motivational interviewing. SPSS and R syntax for weighted negative binomial regression models is included in online supplemental materials.

Background and Aims: The Opioid Use Disorder (OUD) Cascade of Care is a public health model that has been used to measure population‐level OUD risk, treatment engagement, retention, service and outcome indicators. However, no studies have examined its relevance for American Indian and Alaska Native (AI/AN) communities. Thus, we aimed to understand (1) the utility of existing stages and (2) the relative 'fit' of the OUD Cascade of Care from a tribal perspective. Design, Setting, Participants and Measurements: Qualitative analysis of in‐depth interviews with 20 individuals who were knowledgeable regarding the treatment of OUD in an Anishinaabe tribal setting in Minnesota, USA. Community member roles included clinicians, peer support specialists and cultural practitioners, among others. Thematic analysis was used to analyze the data. Findings: Participants identified the key transition points of prevention, assessment, inpatient/outpatient pathways and recovery as relevant to their community. They re‐imagined an Aanji'bide (Changing our Paths) model of opioid recovery and change that was non‐linear; included developmental stage and individual pathways; and demonstrated resilience through connection to culture/spirituality, community and others. Conclusions: Community members living/working in a rural tribal nation in Minnesota, USA identified non‐linearity and cultural connection as key elements to include in an Anishinaabe‐centered model of opioid recovery and change. [ABSTRACT FROM AUTHOR]

Background: Most people with opioid use disorder (OUD) have co-occurring substance use, which is associated with lower receipt of OUD medications (MOUD). Expanding MOUD provision and care linkage outside of substance use disorder (SUD) specialty settings is a key strategy to increase access. Therefore, it is important to understand how MOUD providers in these settings approach care for patients with co-occurring substance use. This qualitative study of Veterans Health Administration (VA) clinicians providing buprenorphine care in primary care, mental health, and pain settings aimed to understand (1) their approach to addressing OUD in patients with co-occurring substance use, (2) perspectives on barriers/facilitators to MOUD receipt for this population, and (3) support needed to increase MOUD receipt for this population. Methods: We interviewed a purposive sample of 27 clinicians (12 primary care, 7 mental health, 4 pain, 4 pharmacists) in the VA northwest network. The interview guide assessed domains of the Tailored Implementation for Chronic Diseases Checklist. Interviews were transcribed and qualitatively analyzed using inductive content analysis. Results: Participants reported varied approaches to identifying co-occurring substance use and addressing OUD in this patient population. Although they reported that this topic was not clearly addressed in clinical guidelines or training, participants generally felt that patients with co-occurring substance use should receive MOUD. Some viewed their primary role as providing this care, others as facilitating linkage to OUD care in SUD specialty settings. Participants reported multiple barriers and facilitators to providing buprenorphine care to patients with co-occurring substance use and linking them to SUD specialty care, including provider, patient, organizational, and external factors. Conclusions: Efforts are needed to support clinicians outside of SUD specialty settings in providing buprenorphine care to patients with co-occurring substance use. These could include clearer guidelines and policies, more specific training, and increased care integration or cross-disciplinary collaboration. Simultaneously, efforts are needed to improve linkage to specialty SUD care for patients who would benefit from and are willing to receive this care, which could include increased service availability and improved referral/hand-off processes. These efforts may increase MOUD receipt and improve OUD care quality for patients with co-occurring substance use. [ABSTRACT FROM AUTHOR]

Background: Measurement-based care (MBC) is the practice of routinely administering standardized measures to support clinical decision-making and monitor treatment progress. Despite evidence of its effectiveness, MBC is rarely adopted in routine substance use disorder (SUD) treatment settings and little is known about the factors that may improve its adoptability in these settings. The current study gathered qualitative data from SUD treatment clinicians about their perceptions of MBC, the clinical outcomes they would most like to monitor in MBC, and suggestions for the design and implementation of MBC systems in their settings. Methods: Fifteen clinicians from one publicly-funded and two privately-funded outpatient SUD treatment clinics participated in one-on-one research interviews. Interviews focused on clinicians' perceived benefits, drawbacks, and ideas related to implementing MBC technology into their clinical workflows. Interviews were audio recorded, transcribed, and coded to allow for thematic analysis using a mixed deductive and inductive approach. Clinicians also completed a card sorting task to rate the perceived helpfulness of routinely measuring and monitoring different treatment outcomes. Results: Clinicians reported several potential benefits of MBC, including improved patient-provider communication, client empowerment, and improved communication between clinicians. Clinicians also expressed potential drawbacks, including concerns about subjectivity in patient self-reports, limits to personalization, increased time burdens, and needing to learn to use new technologies. Clinicians generated several ideas and preferences aimed at minimizing burden of MBC, illustrating clinical changes over time, improving ease of use, and improving personalization. Numerous patient outcomes were identified as "very helpful" to track, including coping skills, social support, and motivation for change. Conclusions: MBC may be a beneficial tool for improving clinical care in SUD treatment settings. MBC tools may be particularly adoptable if they are compatible with existing workflows, help illustrate gradual and nonlinear progress in SUD treatment, measure outcomes perceived as clinically useful, accommodate multiple use cases and stakeholder groups, and are framed as an additional source of information meant to augment, rather than replace, existing practices and information sources. [ABSTRACT FROM AUTHOR]

Substance use disorders (SUDs) are underdiagnosed in healthcare settings. The Substance Use Symptom Checklist (SUSC) is a practical, patient-report questionnaire that has been used to assess SUD symptoms based on Diagnostic and Statistical Manual of Mental Disorders-5th edition (DSM-5) criteria. This study evaluates the test-retest reliability of SUSCs completed in primary and mental health care settings. We identified 1194 patients who completed two SUSCs 1–21 days apart as part of routine care after reporting daily cannabis use and/or any past-year other drug use on behavioral health screens. Test-retest reliability of SUSC scores was evaluated within the full sample, subsamples who completed both checklists in primary care (n=451) or mental health clinics (n=512) where SUSC implementation differed, and subgroups defined by sex, insurance status, age, and substance use reported on behavioral health screens. In the full sample, test-retest reliability was high for indices reflecting the number of SUD symptoms endorsed (ICC=0.75, 95% CI:0.72–0.77) and DSM-5 SUD severity (kappa=0.72, 95% CI:0.69–0.75). These reliability estimates were higher in primary care (ICC=0.81, 95% CI:0.77–0.84; kappa=0.79, 95% CI:0.75–0.82, respectively) than in mental health clinics (ICC=0.74, 95% CI:0.70–0.78; kappa=0.73, 95% CI:0.68–0.77). Reliability differed by age and substance use reported on behavioral health screens, but not by sex or insurance status. The SUSC has good-to-excellent test-retest reliability when completed as part of routine primary or mental health care. Symptom checklists can reliably measure symptoms consistent with DSM-5 SUD criteria, which may aid SUD-related care in primary care and mental health settings. • 1194 patients reported DSM-5 SUD symptoms on Substance Use Symptom Checklists (SUSCs). • SUSCs had high test-retest reliability across settings and demographic subgroups. • Reliability was higher in primary care, where assessment processes were standardized. • SUSCs provide test-retest reliable information about symptoms consistent with DSM-5 SUD. [ABSTRACT FROM AUTHOR]

Background: Most people with alcohol or opioid use disorders (AUD or OUD) are not diagnosed or treated for these conditions in primary care. This study takes a critical step toward quantifying service gaps and directing improvement efforts for AUD and OUD by using electronic health record (EHR) data from diverse primary care organizations to quantify the extent to which AUD and OUD are underdiagnosed and undertreated in primary care practices.Methods: We extracted and integrated diagnosis, medication, and behavioral health visit data from the EHRs of 21 primary care clinics within four independent healthcare organizations representing community health centers and rural hospital-associated clinics in the Pacific Northwest United States. Rates of documented AUD and OUD diagnoses, pharmacological treatments, and behavioral health visits were evaluated over a two-year period (2015-2016).Results: Out of 47,502 adult primary care patients, 1476 (3.1%) had documented AUD; of these, 115 (7.8%) had orders for AUD medications and 271 (18.4%) had at least one documented visit with a non-physician behavioral health specialist. Only 402 (0.8%) patients had documented OUD, and of these, 107 (26.6%) received OUD medications and 119 (29.6%) had at least one documented visit with a non-physician behavioral health specialist. Rates of AUD diagnosis and AUD and OUD medications were higher in clinics that had co-located non-physician behavioral health specialists.Conclusions: AUD and OUD are underdiagnosed and undertreated within a sample of independent primary care organizations serving mostly rural patients. Primary care organizations likely need service models, technologies, and workforces, including non-physician behavioral health specialists, to improve capacities to diagnose and treat AUD and OUD. [ABSTRACT FROM AUTHOR]

Background and aims There is evidence that low-risk drinking is possible during the course of alcohol treatment and can be maintained following treatment. Our aim was to identify characteristics associated with low-risk drinking during treatment in a large sample of individuals as they received treatment for alcohol dependence. Design Integrated analysis of data from the Combined Pharmacotherapies and Behavioral Intervention (COMBINE) study, Project MATCH (Matching Alcoholism Treatments to Client Heterogeneity) and the United Kingdom Alcohol Treatment Trial (UKATT) using repeated-measures latent class analysis to identify patterns of drinking and predictors of low-risk drinking patterns during treatment. Setting United States and United Kingdom. Participants Patients ( n = 3589) with alcohol dependence receiving treatment in an alcohol clinical trial were primarily male (73.0%), white (82.0%) and non-married (41.7%), with an average age of 42.0 (standard deviation = 10.7). Measurements Self-reported weekly alcohol consumption during treatment was assessed using the Form-90 and validated with biological verification or collateral informants. Findings Seven patterns of drinking during treatment were identified: persistent heavy drinking (18.7% of the sample), increasing heavy drinking (9.6%), heavy and low-risk drinking (6.7%), heavy drinking alternating with abstinence (7.9%), low-risk drinking (6.8%), increasing low-risk drinking (10.5%) and abstinence (39.8%). Lower alcohol dependence severity and fewer drinks per day at baseline significantly predicted low-risk drinking patterns [e.g. each additional drink prior to baseline predicted a 27% increase in the odds of expected classification in heavy drinking versus low-risk drinking patterns; odds ratio = 1.27 (95% confidence interval (CI) = 1.10, 1.47, P = 0.002]. Greater negative mood and more heavy drinkers in the social network were significant predictors of expected membership in heavier drinking patterns. Conclusions Low-risk drinking is achievable for some individuals as they undergo treatment for alcohol dependence. Individuals with lower dependence severity, less baseline drinking, fewer negative mood symptoms and fewer heavy drinkers in their social networks have a higher probability of achieving low-risk drinking during treatment. [ABSTRACT FROM AUTHOR]

Young adult frequent cannabis use has increased in prevalence and some frequent users have problems reducing their use. A strong link between momentary craving and subsequent use behaviors among individuals with problematic cannabis use has been reported in the literature, including young adults. In treatment contexts, interventions based on associative learning and reinforcement aim to reduce the prevalence of problematic substance use by altering the association between craving and use by increasing craving management skills such as mindfulness and reducing unhelpful responding such as avoidance or suppression. However, this model has not been tested among young adult cannabis users. The current study examined the influence of trait and state craving management strategies (mindfulness, coping style, experiential avoidance, and craving beliefs) on the link between momentary craving and use, using ecological momentary assessment in a sample of young adults with problematic use interested in reducing their use. Results demonstrated that two craving management constructs were associated with use: non-reactivity (p = 0.02) and non-judgment (p < 0.01). Interactions with momentary craving were observed for two constructs: non-judgmentalness (p = 0.02) and craving beliefs (p < 0.01). Findings suggest that treatments that increase non-reactivity and non-judgmentalness may reduce the occurrence of cannabis use for young adults contemplating reduction during an important period of biopsychosocial development by mitigating the impact of craving or directly reducing use. Additionally, negative beliefs about craving may serve a protective function during acute periods of elevation in momentary craving, an unexpected finding deserving further investigation. [ABSTRACT FROM AUTHOR]

Background: Patients with a substance use disorder (SUD) often present with co-occurring chronic conditions in primary care. Despite the high co-occurrence of chronic medical conditions and SUD, little is known about whether chronic condition outcomes or related service utilization in primary care varies between patients with versus without documented SUDs. This study examined whether having a SUD influenced the use of primary care services and common chronic condition outcomes for patients with diabetes, hypertension, and obesity.Methods: A longitudinal cohort observational study examined electronic health record data from 21 primary care clinics in Washington and Idaho to examine differences in service utilization and clinical outcomes for diabetes, hypertension, and obesity in patients with and without a documented SUD diagnosis. Differences between patients with and without documented SUD diagnoses were compared over a three-year window for clinical outcome measures, including hemoglobin A1c, systolic and diastolic blood pressure, and body mass index, as well as service outcome measures, including number of encounters with primary care and co-located behavioral health providers, and orders for prescription opioids. Adult patients (N = 10,175) diagnosed with diabetes, hypertension, or obesity before the end of 2014, and who had ≥2 visits across a three-year window including at least one visit in 2014 (baseline) and at least one visit occurring 12 months or longer after the 2014 visit (follow-up) were examined.Results: Patients with SUD diagnoses and co-occurring chronic conditions were seen by providers more frequently than patients without SUD diagnoses (p's < 0.05), and patients with SUD diagnoses were more likely to be prescribed opioid medications. Chronic condition outcomes were no different for patients with versus without SUD diagnoses.Discussion: Despite the higher visit rates to providers in primary care, a majority of patients with SUD diagnoses and chronic medical conditions in primary care did not get seen by co-located behavioral health providers, who can potentially provide and support evidence informed care for both SUD and chronic conditions. Patients with chronic medical conditions also were more likely to get prescribed opioids if they had an SUD diagnosis. Care pathway innovations for SUDs that include greater utilization of evidence-informed co-treatment of SUDs and chronic conditions within primary care settings may be necessary for improving care overall for patients with comorbid SUDs and chronic conditions. [ABSTRACT FROM AUTHOR]

Background: Valid, single-item cannabis screens for the frequency of past-year use (SIS-C) can identify patients at risk for cannabis use disorder (CUD); however, the prevalence of CUD for patients who report varying frequencies of use in the clinical setting remains unexplored.Compare clinical responses about the frequency of past-year cannabis use to typical use and CUD severity reported on a confidential survey.Among adult patients in an integrated health system who completed the SIS-C as part of routine care (3/28/2019–9/12/2019; n = 108,950), 5000 were selected for a confidential survey using stratified random sampling. Among 1688 respondents (34% response rate), 1589 who reported past-year cannabis use on the SIS-C were included.We compared patients with varying frequency of cannabis use on the SIS-C (< monthly, monthly, weekly, daily) to survey responses on the Composite International Diagnostic Interview Substance Abuse Module for CUD (any and moderate-severe CUD) and cannabis exposure measures (typical use per-week, per-day). Adjusted multinomial (categorical) and logistic regression (binary), weighted for population estimates, estimated the prevalence of outcomes across frequencies.Patients were predominantly middle-aged (mean = 43.3 years [SD = 16.9]), male (51.8%), white (78.2%), non-Hispanic (94.0%), and commercially insured (68.9%). The prevalence of any and moderate-severe CUD increased with greater frequency of past-year cannabis use reported on the SIS-C (p-values < 0.001) and ranged from 12.7% (6.3–19.2%) and 0.9% (0.0–2.7%) for < monthly to 44.6% (41.4–47.7%) and 20.3% (17.8–22.9%) for daily use, respectively. Greater frequency of use on the SIS-C in the clinical setting corresponded with greater per-week and per-day use on the confidential survey.Among patients who reported past-year cannabis use as part of routine screening, the prevalence of CUD and other cannabis exposure measures increased with greater frequency of cannabis use, underscoring the utility of brief cannabis screens for identifying patients at risk for CUD.Objective: Valid, single-item cannabis screens for the frequency of past-year use (SIS-C) can identify patients at risk for cannabis use disorder (CUD); however, the prevalence of CUD for patients who report varying frequencies of use in the clinical setting remains unexplored.Compare clinical responses about the frequency of past-year cannabis use to typical use and CUD severity reported on a confidential survey.Among adult patients in an integrated health system who completed the SIS-C as part of routine care (3/28/2019–9/12/2019; n = 108,950), 5000 were selected for a confidential survey using stratified random sampling. Among 1688 respondents (34% response rate), 1589 who reported past-year cannabis use on the SIS-C were included.We compared patients with varying frequency of cannabis use on the SIS-C (< monthly, monthly, weekly, daily) to survey responses on the Composite International Diagnostic Interview Substance Abuse Module for CUD (any and moderate-severe CUD) and cannabis exposure measures (typical use per-week, per-day). Adjusted multinomial (categorical) and logistic regression (binary), weighted for population estimates, estimated the prevalence of outcomes across frequencies.Patients were predominantly middle-aged (mean = 43.3 years [SD = 16.9]), male (51.8%), white (78.2%), non-Hispanic (94.0%), and commercially insured (68.9%). The prevalence of any and moderate-severe CUD increased with greater frequency of past-year cannabis use reported on the SIS-C (p-values < 0.001) and ranged from 12.7% (6.3–19.2%) and 0.9% (0.0–2.7%) for < monthly to 44.6% (41.4–47.7%) and 20.3% (17.8–22.9%) for daily use, respectively. Greater frequency of use on the SIS-C in the clinical setting corresponded with greater per-week and per-day use on the confidential survey.Among patients who reported past-year cannabis use as part of routine screening, the prevalence of CUD and other cannabis exposure measures increased with greater frequency of cannabis use, underscoring the utility of brief cannabis screens for identifying patients at risk for CUD.Participants: Valid, single-item cannabis screens for the frequency of past-year use (SIS-C) can identify patients at risk for cannabis use disorder (CUD); however, the prevalence of CUD for patients who report varying frequencies of use in the clinical setting remains unexplored.Compare clinical responses about the frequency of past-year cannabis use to typical use and CUD severity reported on a confidential survey.Among adult patients in an integrated health system who completed the SIS-C as part of routine care (3/28/2019–9/12/2019; n = 108,950), 5000 were selected for a confidential survey using stratified random sampling. Among 1688 respondents (34% response rate), 1589 who reported past-year cannabis use on the SIS-C were included.We compared patients with varying frequency of cannabis use on the SIS-C (< monthly, monthly, weekly, daily) to survey responses on the Composite International Diagnostic Interview Substance Abuse Module for CUD (any and moderate-severe CUD) and cannabis exposure measures (typical use per-week, per-day). Adjusted multinomial (categorical) and logistic regression (binary), weighted for population estimates, estimated the prevalence of outcomes across frequencies.Patients were predominantly middle-aged (mean = 43.3 years [SD = 16.9]), male (51.8%), white (78.2%), non-Hispanic (94.0%), and commercially insured (68.9%). The prevalence of any and moderate-severe CUD increased with greater frequency of past-year cannabis use reported on the SIS-C (p-values < 0.001) and ranged from 12.7% (6.3–19.2%) and 0.9% (0.0–2.7%) for < monthly to 44.6% (41.4–47.7%) and 20.3% (17.8–22.9%) for daily use, respectively. Greater frequency of use on the SIS-C in the clinical setting corresponded with greater per-week and per-day use on the confidential survey.Among patients who reported past-year cannabis use as part of routine screening, the prevalence of CUD and other cannabis exposure measures increased with greater frequency of cannabis use, underscoring the utility of brief cannabis screens for identifying patients at risk for CUD.Main Measures: Valid, single-item cannabis screens for the frequency of past-year use (SIS-C) can identify patients at risk for cannabis use disorder (CUD); however, the prevalence of CUD for patients who report varying frequencies of use in the clinical setting remains unexplored.Compare clinical responses about the frequency of past-year cannabis use to typical use and CUD severity reported on a confidential survey.Among adult patients in an integrated health system who completed the SIS-C as part of routine care (3/28/2019–9/12/2019; n = 108,950), 5000 were selected for a confidential survey using stratified random sampling. Among 1688 respondents (34% response rate), 1589 who reported past-year cannabis use on the SIS-C were included.We compared patients with varying frequency of cannabis use on the SIS-C (< monthly, monthly, weekly, daily) to survey responses on the Composite International Diagnostic Interview Substance Abuse Module for CUD (any and moderate-severe CUD) and cannabis exposure measures (typical use per-week, per-day). Adjusted multinomial (categorical) and logistic regression (binary), weighted for population estimates, estimated the prevalence of outcomes across frequencies.Patients were predominantly middle-aged (mean = 43.3 years [SD = 16.9]), male (51.8%), white (78.2%), non-Hispanic (94.0%), and commercially insured (68.9%). The prevalence of any and moderate-severe CUD increased with greater frequency of past-year cannabis use reported on the SIS-C (p-values < 0.001) and ranged from 12.7% (6.3–19.2%) and 0.9% (0.0–2.7%) for < monthly to 44.6% (41.4–47.7%) and 20.3% (17.8–22.9%) for daily use, respectively. Greater frequency of use on the SIS-C in the clinical setting corresponded with greater per-week and per-day use on the confidential survey.Among patients who reported past-year cannabis use as part of routine screening, the prevalence of CUD and other cannabis exposure measures increased with greater frequency of cannabis use, underscoring the utility of brief cannabis screens for identifying patients at risk for CUD.Key Results: Valid, single-item cannabis screens for the frequency of past-year use (SIS-C) can identify patients at risk for cannabis use disorder (CUD); however, the prevalence of CUD for patients who report varying frequencies of use in the clinical setting remains unexplored.Compare clinical responses about the frequency of past-year cannabis use to typical use and CUD severity reported on a confidential survey.Among adult patients in an integrated health system who completed the SIS-C as part of routine care (3/28/2019–9/12/2019; n = 108,950), 5000 were selected for a confidential survey using stratified random sampling. Among 1688 respondents (34% response rate), 1589 who reported past-year cannabis use on the SIS-C were included.We compared patients with varying frequency of cannabis use on the SIS-C (< monthly, monthly, weekly, daily) to survey responses on the Composite International Diagnostic Interview Substance Abuse Module for CUD (any and moderate-severe CUD) and cannabis exposure measures (typical use per-week, per-day). Adjusted multinomial (categorical) and logistic regression (binary), weighted for population estimates, estimated the prevalence of outcomes across frequencies.Patients were predominantly middle-aged (mean = 43.3 years [SD = 16.9]), male (51.8%), white (78.2%), non-Hispanic (94.0%), and commercially insured (68.9%). The prevalence of any and moderate-severe CUD increased with greater frequency of past-year cannabis use reported on the SIS-C (p-values < 0.001) and ranged from 12.7% (6.3–19.2%) and 0.9% (0.0–2.7%) for < monthly to 44.6% (41.4–47.7%) and 20.3% (17.8–22.9%) for daily use, respectively. Greater frequency of use on the SIS-C in the clinical setting corresponded with greater per-week and per-day use on the confidential survey.Among patients who reported past-year cannabis use as part of routine screening, the prevalence of CUD and other cannabis exposure measures increased with greater frequency of cannabis use, underscoring the utility of brief cannabis screens for identifying patients at risk for CUD.Conclusions: Valid, single-item cannabis screens for the frequency of past-year use (SIS-C) can identify patients at risk for cannabis use disorder (CUD); however, the prevalence of CUD for patients who report varying frequencies of use in the clinical setting remains unexplored.Compare clinical responses about the frequency of past-year cannabis use to typical use and CUD severity reported on a confidential survey.Among adult patients in an integrated health system who completed the SIS-C as part of routine care (3/28/2019–9/12/2019; n = 108,950), 5000 were selected for a confidential survey using stratified random sampling. Among 1688 respondents (34% response rate), 1589 who reported past-year cannabis use on the SIS-C were included.We compared patients with varying frequency of cannabis use on the SIS-C (< monthly, monthly, weekly, daily) to survey responses on the Composite International Diagnostic Interview Substance Abuse Module for CUD (any and moderate-severe CUD) and cannabis exposure measures (typical use per-week, per-day). Adjusted multinomial (categorical) and logistic regression (binary), weighted for population estimates, estimated the prevalence of outcomes across frequencies.Patients were predominantly middle-aged (mean = 43.3 years [SD = 16.9]), male (51.8%), white (78.2%), non-Hispanic (94.0%), and commercially insured (68.9%). The prevalence of any and moderate-severe CUD increased with greater frequency of past-year cannabis use reported on the SIS-C (p-values < 0.001) and ranged from 12.7% (6.3–19.2%) and 0.9% (0.0–2.7%) for < monthly to 44.6% (41.4–47.7%) and 20.3% (17.8–22.9%) for daily use, respectively. Greater frequency of use on the SIS-C in the clinical setting corresponded with greater per-week and per-day use on the confidential survey.Among patients who reported past-year cannabis use as part of routine screening, the prevalence of CUD and other cannabis exposure measures increased with greater frequency of cannabis use, underscoring the utility of brief cannabis screens for identifying patients at risk for CUD. [ABSTRACT FROM AUTHOR]

The high prevalence of opioid use among justice-involved adults make jails an exceptional setting to initiate opioid use disorder (OUD) treatment, but optimal strategies for delivering these interventions are still not well understood. The objective of this study was to conduct a randomized controlled trial to assess the effectiveness of extended-release naltrexone (XR-NTX, Vivitrol®; Alkermes Inc) alone or in conjunction with patient navigation (XR-NTX + PN) for jail inmates with OUD. We randomized a sample of 135 sentenced jail inmates with moderate to severe OUD to (1) XR-NTX only; (2) XR-NTX + PN; or (3) enhanced treatment-as-usual (ETAU) with drug education, each initiated prior to release from jail. We scheduled follow-up data assessments at 1, 3, 6, and 12 months post-release. Primary outcomes were opioid use (based on Timeline Followback Interview and Addiction Severity Index) and meeting CIDI DSM-5 criteria for OUD 6 months postrelease. We also measured treatment adherence, HIV risk, and recidivism. XR-NTX participants received a mean of 2.26 of 7 possible injections compared to XR-NTX + PN participants, who received a mean of 2.93 injections (Cohen's d = 0.33, 95% CI: -0.09 to 0.74). Thirty-six percent of patients in XR-NTX + PN attended at least one postrelease PN session. We found no significant differences by study condition six months after release from jail for the primary outcomes of any opioid use (ETAU: 17%, XR-NTX: 16%, XR-NTX + PN: 29%) and past 30-day OUD (ETAU: 8%, XR-NTX: 11%, XR-NTX + PN: 10%). Secondary outcomes of rearrest and HIV risk also were similar across groups, with the exception of lower sex-related HIV risk among those in the XR-NTX condition at 12 months. This study did not show superior outcomes of XR-NTX or XR-NTX + PN with regard to opioid use or recidivism outcomes, relative to ETAU. It did, however, highlight the difficulties with adherence to XR-NTX and PN interventions in OUD patients initiating treatment in jail. [ABSTRACT FROM AUTHOR]

Co-occurring substance use disorders (SUDs) are common among people with opioid use disorder (OUD) and known to hinder receipt of medications for OUD (MOUD). It is important to understand how MOUD care implemented outside of SUD specialty settings impacts access for patients with co-occurring SUDs. The Veterans Health Administration's (VA) Stepped Care for Opioid Use Disorder Train the Trainer (SCOUTT) initiative was implemented in primary care, mental health, and pain clinics in 18 VA facilities, and was found to increase MOUD receipt. This study assessed the SCOUTT initiative's impact among patients with and without co-occurring SUDs. This study used a controlled interrupted time series design. We extracted electronic health record data for patients with OUD with visits in SCOUTT intervention or matched comparison clinics during the post-implementation year (9/1/2018–8/31/2019). We examined the monthly proportion of patients who received MOUD in SCOUTT intervention or comparison clinics (primary care, mental health, and pain clinics), or in a VA SUD specialty clinic (where patients may have been referred), during the pre- and post-implementation years. Segmented logistic regression models estimated pre-post changes in outcomes (immediate level change from the final month of the pre-implementation period to the first month of the post-implementation period, change in trend/slope) in intervention vs. comparison facilities, adjusting for patient characteristics and pre-implementation trends. We stratified analyses by the presence of co-occurring SUDs. Among patients without co-occurring SUDs, the pre-post trend/slope change in MOUD received in SCOUTT intervention or comparison clinics was greater in intervention vs. comparison facilities (adjusted odds ratio [aOR]: 1.06, 95% confidence interval [CI]: 1.02–1.10), and the immediate increase in MOUD received in SUD clinics was greater in intervention vs. comparison facilities (aOR: 1.12, 95% CI: 1.02–1.22). These changes did not significantly differ in intervention vs. comparison facilities among patients with co-occurring SUDs. The SCOUTT initiative may have increased MOUD receipt primarily among patients without co-occurring SUDs. Focusing on increasing MOUD receipt for patients with co-occurring SUDs may improve the overall effectiveness of MOUD implementation efforts. • SCOUTT implemented MOUD in VA primary care, mental health, and pain clinics. • We examined SCOUTT's impact among patients with and without co-occurring SUD. • SCOUTT may have increased MOUD for patients without, but not with, co-occurring SUD. • MOUD implementation efforts should increase focus on patients with co-occurring SUD. [ABSTRACT FROM AUTHOR]

Brief cannabis screening followed by standardized assessment of symptoms may support diagnosis and treatment of cannabis use disorder (CUD). This study tested whether the probability of a medical provider diagnosing and treating CUD increased with the number of substance use disorder (SUD) symptoms documented in patients' EHRs. This observational study used EHR and claims data from an integrated healthcare system. Adult patients were included who reported daily cannabis use and completed the Substance Use Symptom Checklist, a scaled measure of DSM-5 SUD symptoms (0−11), during routine care 3/1/2015–3/1/2021. Logistic regression estimated associations between SUD symptom counts and: 1) CUD diagnosis; 2) CUD treatment initiation; and 3) CUD treatment engagement, defined based on Healthcare Effectiveness Data and Information Set (HEDIS) ICD-codes and timelines. We tested moderation across age, gender, race, and ethnicity. Patients (N=13,947) were predominantly middle-age, male, White, and non-Hispanic. Among patients reporting daily cannabis use without other drug use (N=12,568), the probability of CUD diagnosis, treatment initiation, and engagement increased with each 1-unit increase in Symptom Checklist score (p's<0.001). However, probabilities of diagnosis, treatment, and engagement were low, even among those reporting ≥2 symptoms consistent with SUD: 14.0% diagnosed (95% CI: 11.7–21.6), 16.6% initiated treatment among diagnosed (11.7–21.6), and 24.3% engaged in treatment among initiated (15.8–32.7). Only gender moderated associations between Symptom Checklist and diagnosis (p=0.047) and treatment initiation (p=0.012). Findings were similar for patients reporting daily cannabis use with other drug use (N=1379). Despite documented symptoms, CUD was underdiagnosed and undertreated in medical settings. • Documentation of cannabis use disorder (CUD) diagnosis and treatment was low. • A DSM-5 Symptom Checklist offered to patients could support diagnosis and treatment. • CUD diagnosis and treatment increased with report of symptoms on the checklist. • Gender moderated associations between reported symptoms and diagnosis and treatment. • There were missed opportunities to identify and treat CUD across all subgroups. [ABSTRACT FROM AUTHOR]

Background: Client language is hypothesized to be a mechanism of action in motivational interviewing (MI). Despite the association of change and sustain talk with substance treatment outcomes, it not known whether providers can intentionally influence this language as hypothesized.Objective: This is a randomized controlled trial to investigate whether substance use providers can be trained to influence client language.Methods: Treatment providers specializing in substance use disorders (n=190) were randomly assigned to standard training in MI (MI-AU) or training emphasizing an influence of client language (MI-LEAF). Treatment sessions with actual clients were evaluated 3, 6 and 12 months after training by masked raters. Frequencies of client change and sustain talk were the outcome variables.Results: Sustain talk, but not change talk, was significantly lower in clients whose providers had received the specialized training (b=-0.175, SE=0.087, p=0.046, CI[-0.348 to 0.002], d=-0.325). Mediation analyses supported a causal chain between a) training, b) providers' attempts to minimize sustain talk in treatment sessions via directive reflective listening and c) client sustain talk in the treatment session (κ2=0.0833, bootstrap SE=0.0394, 95% CI [0.0148, 0.1691]).Conclusions: With specialized training, providers can reduce the amount of opposition language their clients offer when considering a change in their substance use. Demonstrating that client language is under partial control of the provider supports the feasibility of clinical trials to investigate the impact of shaping client language on treatment outcomes. [ABSTRACT FROM AUTHOR]

American Indian communities in Minnesota have been disproportionately impacted by the opioid use disorder (OUD) epidemic, which tribal communities have taken numerous steps to address. The Cascade of Care is a public health framework for measuring population-level OUD risk, treatment engagement, treatment retention, and recovery outcomes, which can help communities monitor the impact of responses to the OUD epidemic and identify where treatment- and recovery-related barriers and facilitators may exist. However, no studies have quantified the Cascade of Care stages within tribal communities and the extent to which these stages can be quantified using existing data sources is unknown. We utilized data from the Minnesota Drug and Alcohol Abuse Normative Evaluation System (DAANES) to quantify OUD Cascade of Care stages for an American Indian tribal nation in Minnesota and for the entire state. DAANES data indicated 269 individuals in the tribal community received treatment for opioid-related problems in 2018. Among them, an estimated 65-99 % initiated medications for OUD and an estimated 13-41 % were retained in treatment for at least 180 days. Existing state-level data can provide information about Cascade of Care stages for American Indian communities, particularly with regard to treatment admission, initiation of medications for OUD, and treatment retention. Additional data sources are needed to measure population-level OUD risk, recovery, and cultural and contextual factors that may impact treatment and recovery. [ABSTRACT FROM AUTHOR]